Estimating co-extinction threats in terrestrial ecosystems.

The biosphere is changing rapidly due to human endeavour. Because ecological communities underlie networks of interacting species, changes that directly affect some species can have indirect effects on others. Accurate tools to predict these direct and indirect effects are therefore required to guide conservation strategies. However, most extinction-risk studies only consider the direct effects of global change-such as predicting which species will breach their thermal limits under different warming scenarios-with predictions of trophic cascades and co-extinction risks remaining mostly speculative. To predict the potential indirect effects of primary extinctions, data describing community interactions and network modelling can estimate how extinctions cascade through communities. While theoretical studies have demonstrated the usefulness of models in predicting how communities react to threats like climate change, few have applied such methods to real-world communities. This gap partly reflects challenges in constructing trophic network models of real-world food webs, highlighting the need to develop approaches for quantifying co-extinction risk more accurately. We propose a framework for constructing ecological network models representing real-world food webs in terrestrial ecosystems and subjecting these models to co-extinction scenarios triggered by probable future environmental perturbations. Adopting our framework will improve estimates of how environmental perturbations affect whole ecological communities. Identifying species at risk of co-extinction (or those that might trigger co-extinctions) will also guide conservation interventions aiming to reduce the probability of co-extinction cascades and additional species losses.

Citizen science and smartphone e-entomology enables low-cost upscaling of mosquito surveillance.

Mosquito surveillance remains a cornerstone of pest and disease control operations globally but is strongly limited in scale by resources. The use of citizen science to upscale scientific data collection is commonplace, and mosquito surveillance programs have begun to make use of citizen scientists in several countries, particularly for exotic species detection. Here we report on a proof of concept trial in southern Australia for a citizen science mosquito surveillance program characterised by fixed point trapping with BG GAT devices and remote mosquito identification through emailed images, which we term 'e-entomology'. In a study with 126 participants, we detected mosquito seasonality with peak abundance in mid-summer (1.78 mosquitoes per trap per day), weather correlations (positive correlation with maximum temperature, r = 0.41) and a diversity of species (15 of 22 known species in the region) in a metropolitan setting. Whilst we demonstrated that the costs of a citizen science program is only about 20% of a comparable professional surveillance program, the mosquito community sampled by citizen scientists was biased towards container-inhabiting species, particularly Aedes notoscriptus. This is the first time fixed-point mosquito trapping has been combined with citizen science e-entomology to deliver comprehensive surveillance of urban mosquitoes.